Computational protocol: Illumina sequencing‐based analysis of sediment bacteria community in different trophic status freshwater lakes

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Protocol publication

[…] Illumina sequence reads were processed using MOTHUR version 1.27.0 (Schloss et al., ). Briefly, upon completing sequencing by the Illumina MiSeq platform, the reads from the original DNA fragments were merged, using FLASH (V1.2.7, http://ccb.jhu.edu/software/FLASH/), and quality filtering of reads was performed according to the literature (Caporaso et al., ). Chimeric reads were removed by checking against a chimera‐free database of 16S rRNA gene sequences, using UCHIME (DeSantis et al., ). Sequences were assigned to the OTUs with a maximum distance of 3%, using MOTHUR (Schloss et al., ). Community diversity indices and rarefaction curve of each sample were generated, using the UPARSE pipeline (Edgar, ). The RDP classifier was used to assign taxonomic identity to the representative sequence for each OTU. [...] The Trophic Status Indices (TSI) (Aizaki, ) of all sampling sites were calculated using the measured Chl‐a, W‐TP, W‐TN, COD, and SD by the following expression: TSI(∑)=∑i=1mwjTSI(j), where TSI(∑) is the completed TSI; w j is the relative weight of TSI of the j parameter; and TSI(j) is TSI of the j parameter. The mean value of all samples in each region was used to represent the local trophic status which, based upon the value of TSI (∑), can be classified as: oligotrophication (0 < TSI≤30), mesotrophication (30 < TSI≤50), light eutrophication (50 < TSI≤60), medium eutrophication (60 < TSI≤70), and hypereutrophication (70 < TSI≤100) on a scale of 0 to 100.The OTU lists of samples were submitted to the LEfSe pipeline (LDA Effect size, http://huttenhower.sph.harvard.edu/galaxy/) to identify significant differential features of seasons or sites (Segata et al., ). Pearson's correlation analysis (SPSS, v20.0) was performed to determine the links between the bacterial community and the environmental factors (S‐TN, S‐NH4, S‐NOx, S‐TP, TOM, P‐NH4, P‐NO3, T, TSI). The correlations between microbial OTU composition and the influential factors were determined by Canonical correspondence analysis (CCA) using CANOCO 4.5. The significance tests of Monte Carlo permutations were conducted to construct the appropriate models of the bacteria–environment relationships. […]

Pipeline specifications

Software tools mothur, UCHIME, UPARSE, RDP Classifier, LEfSe
Applications Metagenomic sequencing analysis, 16S rRNA-seq analysis
Organisms Bacteria, Escherichia coli, Hemisus marmoratus